|
Module 1: Python Programming
Introduction to Python
Variables, Data Types & Operators
Conditional Statements & Loops
Functions & Modules
Strings, Lists, Tuples, Sets & Dictionaries
File Handling & Exception Handling
FObject-Oriented Programming (OOP)
NumPy & Pandas Basics
Module 2: Data Analysis & Visualization
Data Collection & Cleaning
Data Manipulation using Pandas
Data Visualization using Matplotlib & Seaborn
Exploratory Data Analysis (EDA)
Module 3: Artificial Intelligence Fundamentals
Introduction to AI, ML, DL
AI Applications & Industry Use Cases
Problem Solving & Intelligent Systems
AI Ethics & Responsible AI
Module 4: Machine Learning
Introduction to Machine Learning
Supervised Learning / Unsupervised Learning
Regression & Classification
Clustering Techniques
Model Evaluation & Performance Metrics
Module 5: Deep Learning
Neural Networks Fundamentals
Artificial Neural Networks (ANN)
Convolutional Neural Networks (CNN)
Recurrent Neural Networks (RNN)
Deep Learning using TensorFlow & Keras
Module 6: Natural Language Processing (NLP)
Text Preprocessing, Tokenization, Stemming & Lemmatization
Text Classification / Sentiment Analysis
Chatbot Development Basics
Introduction to Large Language Models (LLMs)
Mini Project/ Examination
Project & Final Examination |
